In order to have a first validation of the developed regional model, a test for modelling the effects of a cap on carbon emissions was applied. Thus, a cap on total CO2 emissions was established at the levels of 2006, and the model was run for a 20 years period. Further assumptions were considering that gross domestic product (GDP) would growth around 5% per year until 2026, and establishing a 2% per year growth rate for carbon emissions.
The model allowed calculating the shadow price of CO2 emissions, revealing an increase proportional to the emissions reduction. Among the affected energy sources, emissions from coal would be the most affected by reductions (41% less in2026) and electricity sector would contribute with more than a half of the emission reduction, whereas natural gas would remain the most popular energy source. Therefore, natural gas and raw oil should increase their exportations. On the contrary, this change in the energetic scenario would lead to a big growth of electricity prices (+18%).
From an economical point of view, the restrictions would lead to a slight decrease in productive capacity (0.13 % less in 2026). The most affected sector would be resource producing and transforming sectors, which depend on combustion for their energy inputs. On the contrary, light manufacturing sectors (food, textiles), services and financial sectors would benefit from these measures. Additionally, a substantial welfare loss would take place (0.9 % of national income in 2026), although this effect is lower if gross domestic product is considered instead.
At a regional level, results were disaggregated for the 7 Russian Regions (Central, NorthWest, SouthEast, Volga, Ural, Siberia and Far East) and for 32 economic sectors. Ural Region was the most affected for a cap in emissions, since is very dependent on the mining sector. Its GDP was expected to decrease about 0.9 % in 2026. Other affected regions were Volga and Siberia, although these are less mining dependent. In general terms, a shift to service intensive sectors was expected for the rest of regions, enabling an increase in regional GDP. Nevertheless, the cost in terms of economic activity comes at a substantial gain in environmental benefits.
Running this simulation allowed the SUST-RUS project partners to detect some suitable improvements. Thus, the emission permit price (shadow price) was considered too low, the applied distributive scheme was not redistributive to households, and many of the real policy circumstances of Russia were neglected. Consequently, model was checked and debugged in order to obtain more realistic simulations that could be effectively used in long term strategic planning.
Christophe Heyndrickx, Natalia Tourdyeva and Victoria Alexeeva-Talebi, «The SUST-RUS model: a CGE model on regional level for sustainability policies in Russia »